Chemical sensors have been developed for decades now to detect gases and vapors at various concentration levels for deployment in a wide range of industrial applications. The detection usually centers on a change of a particular property or status of the sensing material (such as temperature, electrical, optical characteristics, etc.) upon exposure to the chemical species of interest. The selection of sensing material itself has spanned across the periodic table with a range of inorganic, semiconducting elements and organic compounds either in bulk or in thin film form. Perhaps the most widely investigated class of sensors is the high temperature metal oxide sensor, due to its high sensitivity with tin oxide as an example of sensor material. The most common SnO2 sensor platform is a chemiresistor wherein the transport characteristics of a conducting channel of tin oxide are modulated by the adsorption of chemical species at elevated temperatures (T≧350° C.). Other types of sensors include electrochemical cells, conducting polymer sensors, surface acoustic wave sensors and catalytic bead sensors.
While commercial sensors based on some of the above approaches are available, research continues on new sensing materials and transducer platforms for improved performance. Desirable attributes of next generation sensors include high sensitivity, in the parts per million (ppm) to parts per billion (ppb) range, low power consumption, room temperature operation, rapid response time, high selectivity and long term stability. Sensors based on the emerging nanotechnology promise to provide improved performance on all of the above metrics compared to the current micro and macro sensors. Nanomaterials exhibit small size, light weight, very high surface to volume ratio, increased chemical reactivity compared to bulk materials, and mechanical stability so that a sensing material can be refreshed or regenerated many times. All these properties are ideal for developing extremely sensitive chemical sensors.
Among the numerous nanomaterials, carbon nanotubes (CNTs) have received significant attention due to their unique electronic and extraordinary mechanical properties. Single-wall carbon nanotubes (SWCNTs) have an enormous surface area, as high as about 1600 m2/gm, which leads to an increased adsorptive capacity for gases and vapors. With all the atoms on the surface, SWCNTs are expected to exhibit a change in properties sensitively upon exposure to the environment. Indeed, electrical conductivity of SWCNTs has been shown to change reproducibly in the presence of gases such as NO2 and NH3. This revelation has resulted in the fabrication of SWCNT-based chemical sensors by several groups.
The principal platform for such sensors has been a nanotube field effect transistor (“CNT-FET”) with a single SWCNT serving as the conducting channel. This platform faces some serious difficulties for commercialization. First, the CNT-FET requires semiconducting SWCNTs for its operation, and selective growth of metallic versus semiconducting nanotubes is not possible today. Second, if an in situ chemical vapor deposition (“CVD”) process is used in the device fabrication sequence, it is hard to make a single SWCNT grow horizontally in order to bridge a given distance between the source and the drain. Alternatively, one is forced to ‘pick and place’ a semiconducting SWNT from bulk samples. Finally, the chemical sensor market is too cost sensitive to rely on complex steps involved in CNT-FET fabrication resulting in low sensor yield and poor reproducibility.
What is needed is an approach using suitably modified nanomaterials, such as SWCNTs, that can detect presence of certain gas components whose presence cannot be detected by any simple means. Preferably, the method should provide high sensitivity (detection of parts per million or parts per billion of the target gas), high selectivity, room temperature operation, low power consumption, high throughput and low cost. Preferably, the method(s) should extend to detection of other gas components with at most modest changes in the nanomaterial modification procedures. Preferably, this method should allow estimation of the effects of change of local temperature, change of local relative humidity and temporal drift (change of baseline and sensitivity with elapsed time).